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SUMMARYThis paper studies synchronization to a desired trajectory for multi-agent systems with second-order integrator dynamics and unknown nonlinearities and disturbances. The agents can have different dynamics and the treatment is for directed graphs with fixed communication topologies. The command generator or leader node dynamics is also nonlinear and unknown. Cooperative tracking adaptive controllers are designed based on each node maintaining a neural network parametric approximator and suitably tuning it to guarantee stability and performance. A Lyapunov-based proof shows the ultimate boundedness of the tracking error. A simulation example with nodes having second-order Lagrangian dynamics verifies the performance of the cooperative tracking adaptive controller.

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